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G J Barton

Publications and source records attributed to G J Barton.

At least 19 recordsLinked to original sources

E-MSD: an integrated data resource for bioinformatics.

The Macromolecular Structure Database (MSD) group (http://www.ebi.ac.uk/msd/) continues to enhance the quality and consistency of macromolecular structure data in the Protein Data Bank (PDB) and to work towards the integration of various bioinformatics data resources. We have implemented a simple form-based interface that allows users to query the MSD directly. The MSD 'atlas pages' show all of the information in the MSD for a particular PDB entry. The group has designed new search interfaces aimed at specific areas of interest, such as the environment of ligands and the secondary structures of proteins. We have also implemented a novel search interface that begins to integrate separate MSD search services in a single graphical tool. We have worked closely with collaborators to build a new visualization tool that can present both structure and sequence data in a unified interface, and this data viewer is now used throughout the MSD services for the visualization and presentation of search results. Examples showcasing the functionality and power of these tools are available from tutorial webpages (http://www. ebi.ac.uk/msd-srv/docs/roadshow_tutorial/).

Algorithms↗

Protein structural domains: analysis of the 3Dee domains database.

The 3Dee database of domain definitions was developed as a comprehensive collection of domain definitions for all three-dimensional structures in the Protein Data Bank (PDB). The database includes definitions for complex, multiple-segment and multiple-chain domains as well as simple sequential domains, organized in a structural hierarchy. Two different snapshots of the 3Dee database were analyzed at September 1996 and November 1999. For the November 1999 release, 7,995 PDB entries contained 13,767 protein chains and gave rise to 18,896 domains. The domain sequences clustered into 1,715 domain sequence families, which were further clustered into a conservative 1,199 domain structure families (families with similar folds). The proportion of different domain structure families per domain sequence family increases from 84% for domains 1-100 residues long to 100% for domains greater than 600 residues. This is in keeping with the idea that longer chains will have more alternative folds available to them. Of the representative domains from the domain sequence families, 49% are in the range of 51-150 residues, whereas 64% of the representative chains over 200 residues have more than 1 domain. Of the representative chains, 8.5% are part of multichain domains. The largest multichain domain in the database has 14 chains and 1,400 residues, whereas the largest single-chain domain has 907 residues. The largest number of domains found in a protein is 13. The analysis shows that over the history of the PDB, new domain folds have been discovered at a slower rate than by random selection of all known folds. Between 1992 and 1997, a constant 1 in 11 new domains deposited in the PDB has shown no sequence similarity to a previously known domain sequence family, and only 1 in 15 new domain structures has had a fold that has not been seen previously. A comparison of the September 1996 release of 3Dee to the Structural Classification of Proteins (SCOP) showed that the domain definitions agreed for 80% of the representative protein chains. However, 3Dee provided explicit domain boundaries for more proteins. 3Dee is accessible on the World Wide Web at http://barton.ebi.ac.uk/servers/3Dee.html.

Computational Biology↗

Estimation of P-values for global alignments of protein sequences.

MOTIVATION: The global alignment of protein sequence pairs is often used in the classification and analysis of full-length sequences. The calculation of a Z-score for the comparison gives a length and composition corrected measure of the similarity between the sequences. However, the Z-score alone, does not indicate the likely biological significance of the similarity. In this paper, all pairs of domains from 250 sequences belonging to different SCOP folds were aligned and Z-scores calculated. The distribution of Z-scores was fitted with a peak distribution from which the probability of obtaining a given Z-score from the global alignment of two protein sequences of unrelated fold was calculated. A similar analysis was applied to subsequence pairs found by the Smith-Waterman algorithm. These analyses allow the probability that two protein sequences share the same fold to be estimated by global sequence alignment. RESULTS: The relationship between Z-score and probability varied little over the matrix/gap penalty combinations examined. However, an average shift of +4.7 was observed for Z-scores derived from global alignment of locally-aligned subsequences compared to global alignment of the full-length sequences. This shift was shown to be the result of pre-selection by local alignment, rather than any structural similarity in the subsequences. The search ability of both methods was benchmarked against the SCOP superfamily classification and showed that global alignment Z-scores generated from the entire sequence are as effective as SSEARCH at low error rates and more effective at higher error rates. However, global alignment Z-scores generated from the best locally-aligned subsequence were significantly less effective than SSEARCH. The method of estimating statistical significance described here was shown to give similar values to SSEARCH and BLAST, providing confidence in the significance estimation. AVAILABILITY: Software to apply the statistics to global alignments is available from http://barton.ebi.ac.uk. CONTACT: geoff@ebi.ac.uk

Databases, Protein↗

3Dee: a database of protein structural domains.

UNLABELLED: The 3Dee database is a repository of protein structural domains. It stores alternative domain definitions for the same protein, organises domains into sequence and structural hierarchies, contains non-redundant set(s) of sequences and structures, multiple structure alignments for families of domains, and allows previous versions of the database to be regenerated. AVAILABILITY: 3Dee is accessible on the World Wide Web at the URL http://barton.ebi.ac.uk/servers/3Dee.html.

Databases, Factual↗

Application of multiple sequence alignment profiles to improve protein secondary structure prediction.

The effect of training a neural network secondary structure prediction algorithm with different types of multiple sequence alignment profiles derived from the same sequences, is shown to provide a range of accuracy from 70.5% to 76.4%. The best accuracy of 76.4% (standard deviation 8.4%), is 3.1% (Q(3)) and 4.4% (SOV2) better than the PHD algorithm run on the same set of 406 sequence non-redundant proteins that were not used to train either method. Residues predicted by the new method with a confidence value of 5 or greater, have an average Q(3) accuracy of 84%, and cover 68% of the residues. Relative solvent accessibility based on a two state model, for 25, 5, and 0% accessibility are predicted at 76.2, 79.8, and 86. 6% accuracy respectively. The source of the improvements obtained from training with different representations of the same alignment data are described in detail. The new Jnet prediction method resulting from this study is available in the Jpred secondary structure prediction server, and as a stand-alone computer program from: http://barton.ebi.ac.uk/. Proteins 2000;40:502-511.

Algorithms↗

ProtEST: protein multiple sequence alignments from expressed sequence tags.

MOTIVATION: An automatic sequence searching method (ProtEST) is described which constructs multiple protein sequence alignments from protein sequences and translated expressed sequence tags (ESTs). ProtEST is more effective than a simple TBLASTN search of the query against the EST database, as the sequences are automatically clustered, assembled, made non-redundant, checked for sequence errors, translated into protein and then aligned and displayed. RESULTS: A ProtEST search found a non-redundant, translated, error- and length-corrected EST sequence for > 58% of sequences when single sequences from 1407 Pfam-A seed alignments were used as the probe. The average family size of the resulting alignments of translated EST sequences contained > 10 sequences. In a cross-validated test of protein secondary structure prediction, alignments from the new procedure led to an improvement of 3.4% average Q3 prediction accuracy over single sequences. AVAILABILITY: The ProtEST method is available as an Internet World Wide Web service http://barton.ebi.ac.uk/servers/protest.html+ ++ The Wise2 package for protein and genomic comparisons and the ProtESTWise script can be found at http://www.sanger.ac.uk/Software/Wise2 CONTACT: geoff@ebi.ac.uk

Amino Acid Sequence↗

Evaluation and improvement of multiple sequence methods for protein secondary structure prediction.

A new dataset of 396 protein domains is developed and used to evaluate the performance of the protein secondary structure prediction algorithms DSC, PHD, NNSSP, and PREDATOR. The maximum theoretical Q3 accuracy for combination of these methods is shown to be 78%. A simple consensus prediction on the 396 domains, with automatically generated multiple sequence alignments gives an average Q3 prediction accuracy of 72.9%. This is a 1% improvement over PHD, which was the best single method evaluated. Segment Overlap Accuracy (SOV) is 75.4% for the consensus method on the 396-protein set. The secondary structure definition method DSSP defines 8 states, but these are reduced by most authors to 3 for prediction. Application of the different published 8- to 3-state reduction methods shows variation of over 3% on apparent prediction accuracy. This suggests that care should be taken to compare methods by the same reduction method. Two new sequence datasets (CB513 and CB251) are derived which are suitable for cross-validation of secondary structure prediction methods without artifacts due to internal homology. A fully automatic World Wide Web service that predicts protein secondary structure by a combination of methods is available via http://barton.ebi.ac.uk/.

Algorithms↗

Protein sequence alignment techniques.

The basic algorithms for alignment of two or more protein sequences are explained. Alternative methods for scoring substitutions and gaps (insertions and deletions) are described, as are global and local alignment methods. Multiple alignment techniques are explained, including methods for profile comparison. A summary is given of programs for the alignment and analysis of protein sequences, either from sequence alone, or from three-dimensional structure.

Algorithms↗

Deposition of macromolecular structures.

Macromolecular structures are being determined at an increasing rate, and are of interest to a wide diversity of researchers. Depositing a macromolecular structure with the Protein Data Bank makes it readily available to the community. Accuracy, consistency and machine-readability of the data are essential, as are clear indications of quality, and sufficient information to allow non-experimentalists to interpret the data. Good-quality depositions are necessary to allow this to be achieved. The PDB's AutoDep system allows deposition and some preliminary automatic checking to take place at multiple sites, prior to full processing and release of the structure by the PDB. However, depositing a structure currently requires the manual entry of a large amount of information at the time of deposition. The data-harvesting approach will allow much more information to be deposited, without placing an additional burden on the depositor. Deposition-ready files will be generated automatically during the course of a structure-determination experiment. The additional information will allow improved validation procedures to be applied to the structures, and the data to be made more useful to the wider scientific community.

Database Management Systems↗

JPred: a consensus secondary structure prediction server.

UNLABELLED: An interactive protein secondary structure prediction Internet server is presented. The server allows a single sequence or multiple alignment to be submitted, and returns predictions from six secondary structure prediction algorithms that exploit evolutionary information from multiple sequences. A consensus prediction is also returned which improves the average Q3 accuracy of prediction by 1% to 72.9%. The server simplifies the use of current prediction algorithms and allows conservation patterns important to structure and function to be identified. AVAILABILITY: http://barton.ebi.ac.uk/servers/jpred.h tml CONTACT: geoff@ebi.ac.uk

Algorithms↗

Conservation of amino acids in multiple alignments: aspartic acid has unexpected conservation.

Analysis of the relationship between surface accessibility and amino acid conservation in multiple sequence alignments of homologous proteins confirms expected trends for hydrophobic amino acids, but reveals an unexpected difference between the conservation of Asp, Glu and Gln. Even when not in an active site, Asp is more highly conserved than Glu. There is a clear preference for conserved and buried Asp to be present in coil, but there is no tendency for Asp to conserve phi/psi in the ++ region of the Ramachandran map. Glu does not show any preference to be conserved in a particular secondary structure. Analysis of recently derived substitution matrices (e.g. BLOSUM) confirms that Glu tends to substitute more frequently with other amino acids than does Asp. Analysis of relative accessibility versus relative conservation for individual amino acid positions in alignments shows a negative correlation for all amino acid types. With the exception of Arg, Lys, Gly, Glu, Asp and Tyr, a relative conservation of > 2 suggests the amino acid will have a relative accessibility of < 50%. Observation of conserved Cys, Gly or Asp in a reliable multiple alignment suggests a position important for the structure of the protein. Furthermore, the Asp is likely to be involved in polar interactions through its side chain oxygen atoms. In contrast, Gln is the least conserved amino acid overall.

Amino Acid Sequence↗

Protein fold recognition by mapping predicted secondary structures.

A strategy is presented for protein fold recognition from secondary structure assignments (alpha-helix and beta-strand). The method can detect similarities between protein folds in the absence of sequence similarity. Secondary structure mapping first identifies all possible matches (maps) between a query string of secondary structures and the secondary structures of protein domains of known three-dimensional structure. The maps are then passed through a series of structural filters to remove those that do not obey simple rules of protein structure. The surviving maps are ranked by scores from the alignment of predicted and experimental accessibilities. Searches made with secondary structure assignments for a test set of 11 fold-families put the correct sequence-dissimilar fold in the first rank 8/11 times. With cross-validated predictions of secondary structure this drops to 4/11 which compares favourably with the widely used THREADER program (1/11). The structural class is correctly predicted 10/11 times by the method in contrast to 5/11 for THREADER. The new technique obtains comparable accuracy in the alignment of amino acid residues and secondary structure elements. Searches are also performed with published secondary structure predictions for the von-Willebrand factor type A domain, the proteasome 20 S alpha subunit and the phosphotyrosine interaction domain. These searches demonstrate how the method can find the correct fold for a protein from a carefully constructed secondary structure prediction, multiple sequence alignment and distant restraints. Scans with experimentally determined secondary structures and accessibility, recognise the correct fold with high alignment accuracy (86% on secondary structures). This suggests that the accuracy of mapping will improve alongside any improvements in the prediction of secondary structure or accessibility. Application to NMR structure determination is also discussed.

Algorithms↗

Crystal structure of isopenicillin N synthase is the first from a new structural family of enzymes.

Penicillin antibiotics are all produced from fermentation-derived penicillins because their chemical synthesis is not commercially viable. The key step in penicillin biosynthesis, in which both the beta-lactam and thiazolidine rings of the nucleus are created, is mediated by isopenicillin N synthase (IPNS), which binds ferrous iron and uses dioxygen as a cosubstrate. In a unique enzymatic step, with no chemical precedent, IPNS catalyses the transfer of four hydrogen atoms from its tripeptide substrate to dioxygen forming, in a single reaction, the complete bicyclic nucleus of the penicillins. We now report the structure of IPNS complexed with manganese, which reveals the active site is unusually buried within a 'jelly-roll' motif and lined by hydrophobic residues, and suggest how this structure permits the process of penicillin formation. Sequence analyses indicate IPNS, 1-aminocyclopropane-1-carboxylic acid oxidase and many of the 2-oxo-acid-dependent oxygenases contain a conserved jelly-roll motif, forming a new structural family of enzymes.

Acremonium↗

Continuous and discontinuous domains: an algorithm for the automatic generation of reliable protein domain definitions.

An algorithm is presented for the fast and accurate definition of protein structural domains from coordinate data without prior knowledge of the number or type of domains. The algorithm explicitly locates domains that comprise one or two continuous segments of protein chain. Domains that include more than two segments are also located. The algorithm was applied to a nonredundant database of 230 protein structures and the results compared to domain definitions obtained from the literature, or by inspection of the coordinates on molecular graphics. For 70% of the proteins, the derived domains agree with the reference definitions, 18% show minor differences and only 12% (28 proteins) show very different definitions. Three screens were applied to identify the derived domains least likely to agree with the subjective definition set. These screens revealed a set of 173 proteins, 97% of which agree well with the subjective definitions. The algorithm represents a practical domain identification tool that can be run routinely on the entire structural database. Adjustment of parameters also allows smaller compact units to be identified in proteins.

Actins↗

Protein secondary structure prediction.

The past year has seen a consolidation of protein secondary structure prediction methods. The advantages of prediction from an aligned family of proteins have been highlighted by several accurate predictions made 'blind', before any X-ray or NMR structure was known for the family. New techniques that apply machine learning and discriminant analysis show promise as alternatives to neural networks.

Animals↗